Jerky driving--An indicator of accident proneness?

This study uses continuously logged driving data from 166 private cars to derive the level of jerks caused by the drivers during everyday driving. The number of critical jerks found in the data is analysed and compared with the self-reported accident involvement of the drivers. The results show that the expected number of accidents for a driver increases with the number of critical jerks caused by the driver. Jerk analyses make it possible to identify safety critical driving behaviour or “accident prone” drivers. They also facilitate the development of safety measures such as active safety systems or advanced driver assistance systems, ADAS, which could be adapted for specific groups of drivers or specific risky driving behaviour.     

Using fuzzy self-organising maps for safety critical systems

This paper defines a type of constrained artificial neural network (ANN) that enables analytical certification arguments whilst retaining valuable performance characteristics. Previous work has defined a safety lifecycle for ANNs without detailing a specific neural model. Building on this previous work, the underpinning of the devised model is based upon an existing neuro-fuzzy system called the fuzzy self-organising map (FSOM). The FSOM is type of ‘hybrid’ ANN which allows behaviour to be described qualitatively and quantitatively using meaningful expressions. Safety of the FSOM is argued through adherence to safety requirements—derived from hazard analysis and expressed using safety constraints. The approach enables the construction of compelling (product-based) arguments for mitigation of potential failure modes associated with the FSOM. The constrained FSOM has been termed a ‘safety critical artificial neural network’ (SCANN). The SCANN can be used for non-linear function approximation and allows certified learning and generalisation for high criticality roles. A discussion of benefits for real-world applications is also presented.     

A method for risk modeling of interdependencies in critical infrastructures

Failures in critical infrastructures may be hazardous to population, economy, and national security. There can be strong interdependencies between various infrastructures, but these interdependencies are seldom accounted for in current risk and vulnerability analyses. To reduce probability and mitigate consequences of infrastructure failures, these interdependencies have to be assessed. The objective of this paper is to present a method for assessing interdependencies of critical infrastructures, as part of a cross-sector risk and vulnerability analysis. The method is based on a relatively simple approach applicable for practitioners, but may be extended for more detailed analyses by specialists. Examples from a case study with the Emergency Preparedness Group of the city of Oslo, Norway, are included.     

A CUSUM chart for detecting the intensity ratio of negative events

This paper developed a single cumulative sum (CUSUM) scheme, called the UCUSUM chart, for simultaneously detecting the size N and time interval T of an event. The new chart used the information of size and frequency of the event and the UCUSUM chart is carried out using the only one statistic U, which contains both T and N; on the other hand, the UCUSUM chart could allocate the detection power to the T shifts and the N shifts. The results present that the UCUSUM chart is significantly powerful compared to other charts which are in the current research with either the time interval T or with the size N. The UCUSUM chart could be applied in many areas including industries and non-industries and the performance of the new chart shows it is much effective in example.     

Determination of the critical absolute blood volume for intradialytic morbid events

The reduction of blood volume below a critical threshold is assumed to trigger intradialytic morbid events (IME). Recently, we presented a simple method to determine the absolute blood volume during routine hemodialysis (HD) carried out without blood sampling and without injection of dyes or radiolabeled markers. Such information could be used to detect excessive volume reduction during HD and to prevent IME. Therefore, we performed a pilot study in IME‐prone patients to identify the absolute blood volume at which they developed clinical symptoms. A volume of 240 mL of ultrapure dialysate was automatically infused into the extracorporeal circulation using the bolus function of a commercial online hemodiafiltration machine incorporating a blood volume monitor (BVM). The increase in relative blood volume (RBV) caused by the infusion was measured and used to determine the absolute blood volume at that time. The blood volume per kilogram body mass at the time of symptomatic IME was also determined. All IME‐prone patients of a single‐dialysis center were included in the study. Ten out of 12 patients became symptomatic at a specific blood volume between 65 and 56 mL/kg (mean 62 mL/kg) whereas RBV showed a wide scatter (82–97%). A specific blood volume of 65 mL/kg seems to represent the threshold for IME by this method. The technique could be completely automated without altering the hardware of the dialysis device. Present feedback systems for automated blood volume‐controlled ultrafiltration could be adapted to maintain absolute blood volume above this critical volume to safely prevent volume‐dependent IME.     

Application of condition-based HRA method for a manual actuation of the safety features in a nuclear power Plant

A practical approach to develop a more realistic fault-tree model with a consideration of various conditions endured by a human operator is proposed. In safety-critical systems, the generation failure of an actuation signal is caused by the concurrent failures of the automated systems and an operator action. These two sources of safety signals are complicatedly correlated. The failures of sensors or automated systems will cause a lack of necessary information for a human operator and result in error-forcing contexts such as the loss of corresponding alarms and indications. It is well known that the error-forcing contexts largely affect the operator's performance. An automated system which consists of multiple processing channels and complex components is also affected by the availability of the sensors. This paper proposes a condition-based human reliability assessment (CBHRA) method in order to address these complicated conditions in a practical way. We apply the CBHRA method to the manual actuation of the safety features such as a reactor trip and auxiliary feedwater actuation in Korean Standard Nuclear Power Plants. Even the human error probability of each given condition is simply assumed, the application results prove that the CBHRA effectively accommodates the complicated error-forcing contexts into the fault trees.     

On the use of non-coherent fault trees in safety and security studies

This paper gives some insights on the usefulness of non-coherent fault trees in system modelling from both the point of view of safety and security.A safety-related system can evolve from the working states to failed states through degraded states, i.e. working state, but in a degraded mode. In practical applications the degraded states may be of particular interest due e.g. to the associated risk increase or the different types of consequent actions. The top events definitions of such states contain the working conditions of some sub-systems/components. How the use of non-coherent fault trees can greatly simplify both the modelling and quantification of these states is shown in this paper. Some considerations about the interpretation of the importance indexes of negated basic events are also briefly described.When dealing with security applications, there is a need to cope not only with stochastic events, such as component failures and human errors, but also with deliberate intentional actions, whose successes might be characterised by high probability values. Different mutually exclusive attack scenarios may be envisaged for a given system. Hence, the essential feature of a fault tree analyser is the capability to determine the exact value of the top event probability containing mutually exclusive events. It is also shown that in these cases the use of non-coherent fault trees allows solving the problem with limited effort.     

Bicyclist safety performance functions for a U.S. city

Efforts have intensified to apply a more evidence-based approach to traffic safety. One such effort is the Highway Safety Manual, which provides typical safety performance functions (SPFs) for common road types. SPFs model the mathematical relationship between frequency of crashes and the most significant causal factors. Unfortunately, the manual provides no SPFs for bicyclists, despite disproportionately high fatalities among this group. In this paper, a method for creating city-specific, bicycle SPFs is presented and applied to Boulder, Colorado. This is the first time a bicycle SPF has been created for a U.S. city. Such functions provide a basis for both future investigations into safety treatment efficacy and for prioritizing intersections to better allocate scarce funds for bicycle safety improvements. As expected, the SPFs show that intersections with higher bicyclist traffic and higher motorist traffic have higher motorist-cyclist collisions. The SPFs also demonstrate that intersections with more cyclists have fewer collisions per cyclist, illustrating that cyclists are safer in numbers. Intersections with fewer than 200 entering cyclists have substantially more collisions per cyclist.     

Use of crash surrogates and exceedance statistics to estimate road safety

The limited ability of existing safety models to properly reflect crash causality has its source in cross-sectional analysis applied to the estimation of the intrinsically complex safety factors with highly aggregated and frequently poor quality of data. The adequacy of the data may be improved thanks to the unprecedented progress in sensing technologies and the invention of the naturalistic driving method of data collection. Proposed in this paper is a new modeling paradigm that integrates several types of safety models. The primary improvement results from a more adequate representation of the crash occurrence process by incorporating crash precursor events into the modeling framework. A Pareto-based estimating method for the likelihood of a collision occurrence, given a precursor event, is explained and illustrated with the simple example of road departures.     

Development of road safety performance indicators for trauma management in Europe

Trauma management (TM) covers two types of medical treatment: the initial one provided by Emergency Medical Services (EMS) and a further one provided by permanent medical facilities. There is a consensus in the professional literature that to reduce the severity and the number of road crash victims, the TM system should provide rapid and adequate initial care of injury, combined with sufficient further treatment at a hospital or trauma centre. Recognizing the important role of TM for reducing road crash injury outcome, it was decided, within the EU funded SafetyNet project, to develop road safety performance indicators (SPIs) which would characterize the level of TM systems’ performance in European countries and enable country comparisons.     

Application of RCM for safety considerations in a steel plant

Any operation or process done on machine or its parts to enhance the efficiency of machine before or after the breakdown is called maintenance. A concern may be said to be successful over the years, when it runs non-interrupted, maintains a smooth production flow consistently and at optimum productivity levels. Plant can achieve productivity up to a satisfactory level by proper maintenance work. The maintenance system may be categorized as either ‘Planned’ or ‘Unplanned‘. The classic maintenance problems in modern industries are insufficient pro-active maintenance, frequent problem repetition, erroneous maintenance work, sound maintenance practices not institutionalized, unnecessary and conservative PM, sketchy rationale for PM actions, lack of traceability/visibility for maintenance program, blind acceptance of OEM inputs, PM variability between like/similar units, paucity of predictive maintenance applications. Hence it was necessary to develop an appropriate methodology to develop strategies and programmatic approach to deal with such problems. The reliability centered maintenance offers the most systematic and efficient process to address an overall programmatic approach to the optimization of plant and equipment maintenanceIn this paper, the concept of RCM has been applied to process of vacuum degassing/vacuum oxygen decarburising (VD/VOD) in steel melting shop of a medium scale steel industry. Safety consideration is the significant aspect for selection of the system. By systematically applying the RCM methodology, failures, failure modes are analyzed. To preserve the system function, preventive maintenance tasks such as inspection/checking, lubrication, cleaning, adjustment, replacement, are allotted for various failure modes. RCM based preventive maintenance schedule for the system is formulated and compared with the company's existing preventive maintenance schedule. For subsystems such as ejectors, water-ring pumps and the RLC/ladle car/furnace, existing maintenance schedule is conservative. For oxygen lance and cooling pumps, maintenance frequency is to be increased to quarterly from yearly in the present schedule. For condensers bimonthly schedule is recommended as compared to none, whereas for cooling pumps the schedule remains unchanged. This reveals that RCM based tasks need not necessarily increase the frequency but can, retain or even decrease the frequency of maintenance based on functional priorities. RCM can also recommend the additional maintenance tasks. Application of RCM based PM schedule requires use of age exploration technique and attitudinal changes.     

The effect of safety climate on seafarers’ safety behaviors in container shipping

This study empirically examined safety climate and its effects on safety behaviors from seafarers’ perceptions in the container shipping context. Research hypotheses were formulated and tested using survey data collected from 608 seafarers working on 124 vessels belonging to 13 of the top 20 global container carriers. A structural equation model was used to examine the effect of safety climate dimensions, namely, safety policy, perceived supervisor safety behavior, and safety management, on safety behavior. The results revealed a positive association between safety climate and seafarers’ safety behavior. The contribution of the study findings to the development of safety climate theory and their managerial implications for vessel safety in shipping operations are discussed.     

Exploring the possibility of a common structural model measuring associations between safety climate factors and safety behaviour in health care and the petroleum sectors

The aim of the present study was to explore the possibility of identifying general safety climate concepts in health care and petroleum sectors, as well as develop and test the possibility of a common cross-industrial structural model. Self-completion questionnaire surveys were administered in two organisations and sectors: (1) a large regional hospital in Norway that offers a wide range of hospital services, and (2) a large petroleum company that produces oil and gas worldwide. In total, 1919 and 1806 questionnaires were returned from the hospital and petroleum organisation, with response rates of 55 percent and 52 percent, respectively. Using a split sample procedure principal factor analysis and confirmatory factor analysis revealed six identical cross-industrial measurement concepts in independent samples—five measures of safety climate and one of safety behaviour. The factors’ psychometric properties were explored with satisfactory internal consistency and concept validity. Thus, a common cross-industrial structural model was developed and tested using structural equation modelling (SEM). SEM revealed that a cross-industrial structural model could be identified among health care workers and offshore workers in the North Sea. The most significant contributing variables in the model testing stemmed from organisational management support for safety and supervisor/manager expectations and actions promoting safety. These variables indirectly enhanced safety behaviour (stop working in dangerous situations) through transitions and teamwork across units, and teamwork within units as well as learning, feedback, and improvement. Two new safety climate instruments were validated as part of the study: (1) Short Safety Climate Survey (SSCS) and (2) Hospital Survey on Patient Safety Culture-short (HSOPSC-short). Based on development of measurements and structural model assessment, this study supports the possibility of a common safety climate structural model across health care and the offshore petroleum industry.     

A method for determining the fatigue critical plane for biaxial random vibration in the frequency domain

This paper provides a direct method to determine the critical plane orientation for biaxial random vibration. The critical plane is obtained by finding the direction that maximizes the normal stress variance. It is found that the shear stress is uncorrelated with the normal stress in this orientation. Furthermore, the direction of maximal normal stress is shown to coincide with the principal direction in the case of proportional stress components. Spectral fatigue damage methods proposed in recent literature involve a Monte Carlo enumeration step to find the critical plane orientation. By using the proposed technique, computationally expensive enumeration methods are avoided and greater accuracy in the fatigue damage estimate may result.     

The safety climate and its relationship to safety practices, safety of the work environment and occupational accidents in eight wood-processing companies

Employees continuously observe their work environment and the actions of their fellow workers and superiors, and they use such observations as a basis for the creation of cognitive models associated with safety. These models regulate their actions in the workplace and thus have an influence on safety. This study attempts to define the structure of the safety climate as perceived by workers and the correlations between the safety climate, on the one hand, and the safety practices of the company, the safety level of the work environment and occupational accidents on the other. The variables used in this study were the same as those employed in two previous Finnish safety climate studies carried out in the plywood industry, shipyards, the forestry industry, building construction and stevedoring. The safety climate was measured by means of a questionnaire. Workers from four sawmills, two plywood factories and two parquet plants participated. The total number of participants was 508 in 1990 and 548 in 1993. The variables formed four factors, whose contents and reliabilities closely resembled the results obtained in the earlier studies. These results indicate that the structure of the safety climate among Finnish workers is quite stable. The safety climate correlated both with the safety level of the work environment and with the safety practices of the company, but the correlation between the safety climate and the safety of the work environment was stronger. This result differs from those of the previous studies, in which the safety climate was defined specifically in terms of an individual’s perceptions of the safety practices of the company and of the behavior of other employees. The two safety climate factors that described a company’s attitudes to safety and its safety precautions correlated with the accident rates. The better the safety climate of the company was, the lower was the accident rate. Four companies with an accident rate below the average for the wood-processing industry had a better safety climate than four similar companies with an accident rate above the average.     

Dynamic modeling of the tradeoff between productivity and safety in critical engineering systems

Short-term tradeoffs between productivity and safety often exist in the operation of critical facilities such as nuclear power plants, offshore oil platforms, or simply individual cars. For example, interruption of operations for maintenance on demand can decrease short-term productivity but may be needed to ensure safety. Operations are interrupted for several reasons: scheduled maintenance, maintenance on demand, response to warnings, subsystem failure, or a catastrophic accident. The choice of operational procedures (e.g. timing and extent of scheduled maintenance) generally affects the probabilities of both production interruptions and catastrophic failures. In this paper, we present and illustrate a dynamic probabilistic model designed to describe the long-term evolution of such a system through the different phases of operation, shutdown, and possibly accident. The model's parameters represent explicitly the effects of different components' performance on the system's safety and reliability through an engineering probabilistic risk assessment (PRA). In addition to PRA, a Markov model is used to track the evolution of the system and its components through different performance phases. The model parameters are then linked to different operations strategies, to allow computation of the effects of each management strategy on the system's long-term productivity and safety. Decision analysis is then used to support the management of the short-term trade-offs between productivity and safety in order to maximize long-term performance. The value function is that of plant managers, within the constraints set by local utility commissions and national (e.g. energy) agencies. This model is illustrated by the case of outages (planned and unplanned) in nuclear power plants to show how it can be used to guide policy decisions regarding outage frequency and plant lifetime, and more specifically, the choice of a reactor tripping policy as a function of the state of the emergency core cooling subsystem.     

The development of railway safety in Finland

This study reviews the development of railway safety in Finland from 1959 to 2008. The results show that the level of safety has greatly improved over the past five decades. The total number of railway fatalities did not show any obvious decreasing or increasing trend during the first decade, but since the early 1970s the annual number of fatalities has decreased from about 100 to 20. The estimated overall annual reduction per year from 1970 to 2008 was 5.4% (with a 95% confidence interval from −8.2% to −2.6%). The reduction in subcategories per million train-kilometres from 1959 to 2008 was 4.4% per year for passengers, 8.3% for employees, 5.0% for road users at level crossings and 3.6% for others (mainly trespassers). The safety improvement for passengers and staff was probably influenced by the introduction of central locking of doors in passenger cars and improved procedures to protect railway employees working on the tracks. The number of road users killed at level crossings has fallen due to the installation of barriers and the construction of overpasses and underpasses at crossings with dense traffic, removal of level crossings, and an improvement of conditions such as visibility at crossings. The number of trespasser fatalities has seen the least decline. Key plans for the future include further reduction of the number of level crossings on the state railway network from the current roughly 3500–2200 by 2025, and involving communities in safety work related to railway trespassers.     

Development of a safety critical software requirements verification method with combined CPN and PVS: a nuclear power plant protection system application

Safety-critical software systems such as certain nuclear instrumentation and control (NI&C) systems should be developed with thorough verification. This study presents a method of software requirement verification with a case study for a nuclear power plant (NPP) protection system. The verification introduces colored petri net (CPN) for system modeling and prototype verification system (PVS) for mathematical verification. In order to aid flow-through from modeling by CPN to mathematical proof by PVS, an information extractor from CPN models has been developed in this paper. In order to convert the extracted information to the PVS specification language, a translator has also been developed. This combined method has been applied to the functional requirements of the Wolsong NPP Shut Down System #2 (SDS2); logical properties of the requirements were verified. Through this research, guidelines and a tool support for the use of formal methods have been developed for application to NI&C software verification.